tests/benchmark/NEON/DirectConvolutionLayer.cpp

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#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "tests/NEON/Accessor.h"
#include "tests/benchmark/fixtures/ConvolutionLayerFixture.h"
#include "tests/datasets/DirectConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "utils/TypePrinter.h"

namespace arm_compute
{
namespace test
{
namespace benchmark
{
namespace
{
// Special data types for networks that need 5x5 direct convolution, which does not support Fixed Point
#ifdef ARM_COMPUTE_ENABLE_F16
const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 });
#else  /* ARM_COMPUTE_ENABLE_F16 */
const auto data_types = framework::dataset::make("DataType", { DataType::F32 });
#endif /* ARM_COMPUTE_ENABLE_F16 */
} // namespace

using NEConvolutionLayerFixture = ConvolutionLayerFixture<Tensor, NEDirectConvolutionLayer, Accessor>;

TEST_SUITE(NEON)

REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL,
                                framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", 1)));

REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL,
                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", 1)));

REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL,
                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", 1)));

REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL,
                                framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", 1)));

TEST_SUITE(NIGHTLY)
REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
                                framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", { 4, 8 })));

REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", { 4, 8 })));

REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", { 4, 8 })));

REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
                                framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", { 4, 8 })));

REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
                                framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", { 1, 2 })));

REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), data_types),
                                                            framework::dataset::make("Batches", { 1, 4, 8 })));

TEST_SUITE_END()
TEST_SUITE_END()
} // namespace benchmark
} // namespace test
} // namespace arm_compute